Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling

Song Liu,Lisheng Yang,Qingping Jiang,Haowei Wu,Shizhong Yang

doi:10.1155/2016/8109013

Abstract

A blind direction-of-arrival (DOA) estimation algorithm based on the estimation of signal parameters via rotational invariance techniques (ESPRIT) is proposed for a uniform circular array (UCA) when strong electromagnetic mutual coupling is present. First, an updated UCA model with mutual coupling in a discrete Fourier transform (DFT) beam space is deduced, and the new manifold matrix is equal to the product of a centrosymmetric diagonal matrix and a Vandermonde-structure matrix. Then we carry out blind DOA estimation through a modified ESPRIT method, thus avoiding the need for spatial angular searching. In addition, two mutual coupling parameter estimation methods are presented after the DOAs have been estimated. Simulation results show that the new algorithm is reliable and effective especially for closely spaced signals.

Highlights

Uniform circular array based DOA estimation methods are always attractive because the uniform circular array (UCA) has a special symmetric structure that provides almost the same resolution ability along the 360∘ azimuth angle domain
A classic DOA estimation method based on an iterative search technique was proposed to estimate the DOA and the mutual coupling matrix (MCM) parameters jointly [7], but it has a high computation cost
First we introduce the discrete Fourier transform (DFT) of the MCM for UCA

Summary

Introduction

Uniform circular array based DOA estimation methods are always attractive because the UCA has a special symmetric structure that provides almost the same resolution ability along the 360∘ azimuth angle domain. Except for conventional DOA estimation methods such as beam space searching or the Capon method [1], many other methods can be applied, such as the commonly used multiple signal classification (MUSIC) [2] or the well-known ESPRIT [3] in phase mode space. More effective methods such as UCA-RBMUSIC and UCA-ESPRIT [4] have been introduced, and the mapping error reducing method was developed [5]. We will introduce two methods to estimate the MCM parameters once the DOA values are calculated

UCA Model with Mutual Coupling

Algorithm

Simulations

Conclusion